Evolutionary Game Analysis of the Realization of Health Big Data Value and Governance Implications
Year: 2026
Type: article
Abstract: The realization of the value of health big data relies on the coordinated cooperation among patients, the government, and data users. Enhancing the symmetry and balance between patient participation and the compliant use of data by data users is a critical link. This paper constructs a tripartite evolutionary game model and employs MATLAB R2023a simulation to analyze the impact of factors such as initial willingness, compliance costs, and penalties for violations on the strategic choices of the game players and the evolution of the system. The findings reveal that: (1) Patient participation is a key condition for achieving an ideal equilibrium in the system. (2) The data service income from participating in data provision and the costs associated with privacy breaches are critical factors influencing patients’ strategic choices. (3) Penalties for violations are a crucial factor in ensuring that data users choose compliant utilization; however, when compliance costs are high, their constraining effect may be somewhat diminished. (4) Enhancing regulatory efficiency is the future direction for government departments. Based on these findings, countermeasures and suggestions are proposed, including trust building, technological innovation and differentiated supervision, and constructing trusted data spaces, to provide references for health big data governance.
Source: Symmetry
DOI: 10.3390/sym18050701
Authors: Dandan Wang, Hao Li, Jun Ma
Institution: Henan University of Science and Technology
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G2236717107
OpenAlex ID: W7155163948
